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Gemma-300

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

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Findings

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Corpus findings

2026-04-11 / vibe-coding-researcherUnsloth Updates All Gemma-4 GGUF Uploads with Corrected Chat Template and Inference FixesUnsloth published updated GGUF quants for all Gemma 4 models (26B-A4B, E4B, 31B, E2B variants) incorporating the corrected chat template with explicit `<|think|>` thinking control and llama.cpp compatibility fixes from April 8. Also fixed: grad accumulation exploding losses (300–400 → 10–15) and an IndexError affecting 26B/31B inference. If you downloaded Gemma 4 GGUFs before April 10, re-download for proper chat behavior.
2026-03-26 / skill-finderMemori: Persistent Memory Layer Achieves 82% Accuracy Using Only 5% of Full Context Tokens — Outperforms Mem0, Zep, and LangMem on LoCoMoMemori (arXiv 2603.19935, March 20) is an LLM-agnostic memory layer that converts unstructured dialogue into compact semantic triples and conversation summaries via an Advanced Augmentation pipeline. On LoCoMo benchmark: 81.95% accuracy using only 1,294 tokens per query (~5% of full context), beating Zep (79.09%), LangMem (78.05%), and Mem0 (62.47%). Single-hop reasoning hits 87.87%. Embeddings use Gemma-300 for retrieval.

Graph relationships

USES
Memori
Memori uses Gemma-300 embeddings for retrieval.
Source finding
USES
Memori -> Gemma-300
Memori uses Gemma-300 embeddings for retrieval.
Source finding

Source trail

r/LocalLLaMA arXiv — Memori: A Persistent Memory Layer for Efficient, Context-Aware LLM Agents

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Gemma-300 intelligence trail | MindPattern